This paper studies the distribution of income in Indian states and explores the dynamics underlying income inequality, especially focusing on changes in bottom incomes over time. While economic inequality has been an animating concern underlying economic policymaking in independent India, the lack of periodic income data has been a significant impediment in understanding the true nature and extent of the phenomenon (Banerjee and Piketty 2005; Chancel and Piketty 2019; Deaton and Drze 2002; Kohli 2012; Dev and Ravi 2007; Sahasranaman and Jensen 2021). In this context, measurement of inequality in India has been limited to consumption inequality, obtained from the regularly conducted National Sample Surveys (NSS). More recently, the two rounds of the India Human Development Survey (IHDS) provide a nationally representative panel with income data for 200405 and 201112. Using multiple sources, including tax records, NSS, and IHDS, Chancel and Piketty (2019) constructed the Indian income distribution for 19222015, thus producing the longest-yet time series of income for India. Using this, they were able to quantify the extent of increase in income inequality since the 1980s, which saw top 10% of incomes increasing their share from 31% of total income in 1981 to 56% in 2015 (Chancel and Piketty 2019). While these data make possible a study of income inequality at the coarse-grained national level, they still do not provide a representative picture of the income distribution at finer-grained subnational levels of the state and the district. At the level of states, the literature on income distributions is sparse, with extant work primarily using the NSS consumption data to study consumption inequality across states. Comparing consumption inequality across 17 states in the pre- and post-reform periods (19832005), it was found that inequality either increased or declined at a slower pace in the post-reform period in most states (Dev and Ravi 2007). States with low poverty like Kerala, Punjab, and Jammu and Kashmir (J&K) were found to have higher income and inequality elasticities, implying that continued poverty reduction would require reduction in inequality in addition to growth; while states with high poverty such as Uttar Pradesh (UP), Bihar, and Madhya Pradesh (MP) had low income and inequality elasticity, meaning that growth was more important than redistribution in these states (Dev and Ravi 2007). Using the NSS data for 19992000 to 200607, consumption inequality was found to increase with rising state incomes (Arora 2011). Between 199394 and 200405, intra-state consumption inequality was found to have increased in Gujarat, Haryana, Kerala, Odisha, and Punjab (Dubey 2009). In the absence of income data, non-economic data such as night-time lights have also been used to proxy regional income, and based on this method, southern and western regions of India were found, on average, to have a higher income inequality than other parts of the country (Singhal et al 2020). While the lack of data constrains our ability to study long-term trends in state-level income, it is now possible to empirically construct and examine recent state-level income distributions using data from the Consumer Pyramids Household Survey (CPHS)a household panel survey representative at the level of states, which has been capturing income data since 2014.